In recent years, the increasing interest and requirements for improved engine diagnostics and control has led to the implementation of several different sensing and signal processing technologies. In order to optimize the performance and emission of an engine, detailed and specified knowledge of the combustion process inside the engine cylinder is required. In that sense, the torque generated by each combustion event in an IC engine is one of the most important variables related to the combustion process and engine performance.
In-cylinder pressure and engine torque have been recognized as fundamental performance variables in internal combustion engines for many years now. Conventionally, the in-cylinder pressure has been directly measured using in-cylinder pressure transducers in a laboratory environment. Then, the indicated torque has been calculated from the measured in-cylinder pressure based on the engine geometry while the net engine torque has been obtained considering the torque losses. However, such direct measurements using conventional pressure sensors inside engine combustion chambers are not only very expensive but also not reliable for production engines. For this reason, practical applications based on these fundamental performance variables in commercially produced vehicles have not been established yet. Therefore, instead of employing the expensive yet not reliable conventional approach, there is a need for different approaches of obtaining and using such performance variables by estimating the net cylinder torque resulting from each combustion event while utilizing pre-existing sensors and easily accessible engine state variables, such as the instantaneous angular position and velocity of the crankshaft. This approach enhances the on-board and real-time estimations of engine state variables such as instantaneous torque in each individual cylinder and bring out many possible event-based applications for electronic throttle control, cylinder deactivation control, transmission shift control, misfire detection, and general-purpose condition monitoring and diagnostics [1-3].
The crankshaft of an IC engine is subjected to complex forces and torque excitations created by the combustion process from each cylinder. These torque excitations cause the engine crankshaft to rotate at a certain angular velocity. The resulting angular speed of engine crankshaft consists of a slowly varying mean component and a quickly varying fluctuating component around the mean value, caused by the combustion events in each individual cylinder [4]. Outcome of the torque estimation approaches strongly relies on the ability to correlate the characteristics of the crankshaft angular position, speed, and its fluctuations to the characteristics of actual cylinder torque [3] and [4]. Over the past years, this torque estimation problem has been investigated by numerous researchers explicitly or implicitly, inverting an engine dynamic model of various complexities. Those researchers have successfully developed and validated the dynamic models describing the cylinder torque to the crankshaft angular velocity dynamics in internal combustion engines.
One of the earliest strategies targeted at developing the engine and crankshaft dynamic model allowing the speed-based torque estimation was carried out by Rizzoni, who introduced the possibility of accurately estimating the mean indicated torque by a two-step procedure [4]. It consists of first deconvolving the measured crankshaft angular velocity through the rotational dynamics of the engine to obtain the net engine torque which accelerates the crankshaft, and then of converting this net torque to indicated torque through a correction for the inertia torque component, caused by the reciprocating motion of crank-slider mechanism, and for piston/ring friction losses. Another strategy was introduced focusing on reconstructing the instantaneous as well as average engine torque based on the frequency-domain deconvolution method [3]. However, this method required pre-computation of the frequency response functions relating crankshaft speed to indicated torque in the frequency-domain and storing their inverses in a mapping format, which has difficulties of determining the frequency functions experimentally. An approach bypassing this difficulty was proposed by Srinivasan et al. using the repetitive estimators [5]. Further studies of the speed-based torque estimation was continued by Kao and Moskwa, and Rizzoni et al. through the use of nonlinear observers, particularly sliding mode observers [6] and [7]. This method of the nonlinear observer was desirable for variable speed applications since a wide range of operating conditions required the non-linearity of the models. Other torque estimation efforts involving an observer were based on the use of the unknown input observer by Rizzoni et al. [8-10]. This method was, however, only applicable to constant speed (or near constant speed) engines. One of the most recent research efforts aimed at the individual cylinder pressure and torque estimations was based on the stochastic approach by Guezennec and Gyan [1] and [11]. This approach permitted estimations of the instantaneous in-cylinder pressure accurately without any significant computational requirement based on the correlations between in-cylinder pressure and crankshaft speed variations.
Even though all these approaches described previously were successful over the past years, most of them were not feasible for the on-board real-time estimation and control in mass-production engines. In other words, these approaches can only be practically implemented in a post-processing phase because they must involve either highly resolved measurements of the crankshaft speed or significant amounts of computational requirements. The present invention, however, presents a practical and applicable way of implementing the speed-based torque estimation technique on a production engine in order to develop a methodology and algorithm extracting the in-cylinder pressure and indicated torque information from a less resolved/sampled crankshaft speed measurement for the purpose of real-time estimation and engine control in production vehicles. Two different approaches have been implemented, namely “Stochastic Estimation Technique” and “Frequency-Domain Analysis,” to estimate the instantaneous indicated torque (as well as in-cylinder pressure) in real time based on the crankshaft speed fluctuation measurement. An overview of both techniques is presented. Next, their implementations on an in-line four-cylinder spark-ignition engine are presented under a wide range of engine operating conditions such as engine speed and load. Then, validations of the robustness of these techniques are presented through the real-time estimation of indicated torque during the actual engine operations, demonstrating that these methods have very high potential for event-based engine controls and diagnostics in mass-production engines.